Hybrid Multiobjective Optimization Using Deterministic and Metaheuristic Techniques for Flowback Water Reusing in Hydraulic Fracturing Processes

Abstract

This paper presents a new optimization framework that reconciles deterministic and metaheuristic optimization in order to solve nonconvex models. In this way, it is possible to solve the convex part in a software specialized in deterministic optimization and the nonconvex part using metaheuristic tools. The chosen software for the deterministic optimization part was general algebraic modeling system (GAMS), and the metaheuristic optimization algorithm is the improved multiobjective differential evolution (I-MODE) coded in visual basic for applications (VBA). Likewise, a linking strategy is proposed through VBA code to execute the GAMS solver. The new solution strategy consists in manipulating the data that serve as parameters in the problem to be solved in the GAMS platform and evaluating the performance of the optimal values of the objective functions in the I-MODE algorithm with updated values for the involved parameters. The proposed methodology is applied to the hydraulic fracturing (HF) process to obtain shale gas. The problem related to HF process corresponds to the use of fresh water necessary for the extraction of shale gas, as well as the type of technology that can be used in the treatment of flowback water. The mathematical model that optimizes the return water management problem is solved using deterministic optimization, while the scheduling is fixed using evolutionary algorithms of metaheuristic optimization strategies. The obtained results offer attractive alternatives for the specified objective functions in an acceptable computation time.

[Retracted] Application of Computer Simulation Optimization Algorithm in Waste Treatment of Drilling Engineering

“…At the end of the injection, the well or annulus is sealed with cement. is technique is more demanding and expensive to treat, and the drill cuttings reinjection technique may cause contamination to groundwater or the formation; for example, during drill cuttings reinjection, the reinjected slurry may leak through natural fractures, hydraulically fractured fractures, and poorly cemented parts of the well, thus causing contamination to groundwater and the formation [9]. e centralized treatment method is a common treatment method used in developed countries such as the United States.…”

Multi-objective Optimization Approach Based on Deterministic and Metaheuristic Techniques to Resource Management in Health Crisis Scenarios Under Uncertainty

“…For this purpose, the LPC is composed of a set of subroutines or macros developed in VBA that allow the exchange of data between the MOA and the DOA, that is, between the GAMS software and the MS Excel platform. The set of macros that allow the linking of programs can be complicated; therefore, if a more detailed explanation of the particular methodology for linking the MOA with the DOA is required, more detailed information about it can be found in Hernández-Pérez et al ( 2020 ). Objective function values calculation by DOA: In DOA, the single-objective optimization process is carried out.…”

“…These lines of code are grouped into sub routines that are called by a main module. More detailed information about it can be found in Hernández-Pérez et al ( 2020 ).…”

“…Recently, the solution of a complex optimization problem has been reported, which consists in the optimal management of an essential resource, water (Hernández-Pérez et al 2020 ). In that work, a general methodology that allows to link deterministic optimization with metaheuristics was used.…”

Use of Statistic Functions to Consider Uncertainty in Multi-objective Optimization Methods Based on Metaheuristic Algorithms

“…Additionally, a series of hybrid algorithms (Takahama et al 2005) have been developed to solve complex and nonlinear problems (Chen et al 1992). Recently, metaheuristic optimization techniques have been used for designing new hybrid methodologies that suit deterministic search methods and metaheuristic optimization (Hernández-Pérez et al 2020), for example, the hybrid multi-objective Bayesian estimation of distribution algorithm (Martins et al 2021), the hybrid genetic algorithm (Ha et al 2020), and the hybrid adaptive large neighborhood search algorithm (Masmoudi et al 2020).…”